Correlation Analysis of Manufacturing Systems

9812858Altiok这是一个研究制造系统中相关性(作为时间依赖性的代理)对性能影响的项目。该项目将确定制造系统中具有明显相关性的随机组件；将研究其对性能统计的影响；并将开发建模技术，以便在相关性显著时捕捉这些相关性。潜在的随机成分包括客户需求、订单加载时间、机器故障和停机时间的随机过程。该项目将采用一种新的建模方法，称为TES/QTES，它强调对这些随机过程中的相关性进行显式建模。TES过程构成了一类用途广泛的连续空间、离散时间随机过程，旨在同时捕捉经验分布和自相关，而QTE本质上是TES的离散化变体，适合于分析建模。该方法将应用于包括制药、食品加工和微电子在内的各种行业，以获得性能指标的解析和/或数值解决方案。它将被进一步用来探索相关性对各种制造业绩衡量标准和最优运营政策的影响。如果成功，这项研究将产生一种新的以关联为导向的范式。相关性分析，旨在影响制造研究和实践。研究TES/QTES模型有望产生更准确的制造系统分析或仿真模型以及相关的制造系统性能预测。改进的预测将使生产计划、调度和库存控制更加有效。所研究的相关分析的实际方面将与工业伙伴合作进行。从教育角度来看，相关分析将纳入与制造相关的理论和应用的本科生和研究生课程，包括模拟、生产控制、库存理论和绩效分析。

9812858Altiok This grant fluids a project to study tile performance effects of correlations (as proxies of temporal dependence) in manufacturing systems. The project will identify random components of manufacturing systems with appreciable correlations; will study their impact on performance statistics; and will develop modeling technologies to capture correlations whenever present in appreciable magnitudes. Potential random components include stochastic processes of customer demands, order load times, machine failures and down times The project will employ a novel modeling methodology, called TES/QTES, which emphasizes explicit modeling of correlations in such stochastic processes. TES processes constittute a versatile class of continuous-space, discrete-time stochastic processes designed to capture empirical distributions and autocorreclations, simultaneously, while QTES is essentially a discretized variant of TES, suitable for analytical modeling. The methodology will be applied to various industries including pharmaceutical, food processing and microelectronics, to obtain analytical and/or numerical solutions for performance metrics. It will farther be used ti explore the impact of correlations on various manufacturing performance measures and optimal operating policies. If successful, this research will produce a new correlation-oriented paradigm. correlation analysis, designed to impact both manufacturing research and practices. The research TES/QTES models promise to yield significantly more accurate analytical or simulation models of manufacturing systems and associated performance predictions in manufacturing systems. Improved predictions will faxcilitate more effective production planning, scheduling and inventory control. The practical aspects of the researched correlation analysis will be exercised in collaboration with industrial partners. From The educational viewpoint, correlation analysis will be incorporated into undergraduate and graduate courses on manufacturing-related theory and applications, including simulation, production control, inventory theory and performance analysis.